Can player profiling technology bring about a brighter future for online poker?

Can player profiling technology bring about a brighter future for online poker?

There is a game that we all love. Recent cheating scandals have shown that more needs to be done to weed out bad actors. Long-term growth can only come from attracting new players and persuading them to stick around. They will only be able to do that if the games they are playing are fun, fair, and beatable.

A5 Labs has a solution for all of the above, with a novel blueprints for player profiling that extends far beyond game security, suggesting a potential revolution in everything from table selection to loyalty rewards. It involves profiling players not just on risk, but on value as well. In its white paper, Advanced Technologies for Secure, Fair, and Fun Online Poker, the full details are available. Here is the way it works.

How player profiling technology works

The A5 paper contains three key ideas for player profiling. For very broad, very rough categorizations, there is contextual data. There is a method for analyzing hand geometry. There is machine learning that can drive efficiency and accuracy.

Textual data can be used to assess your internet footprint as a poker player. What kind of device you are on, where your address is located, and whether or not you have other software interacting with the poker platform are some of the things that come to mind. Information like your win rate, how often you enter a pot, and how often you three-bet from the big blind would be included in this.

The sites can do a quick risk assessment with data like this. The fact that there are multiple logins from the same address is likely to cause coluders in the same building to use a virtual private network. It would raise your risk if you used a virtual private network. A player with a VPIP of 30% from under the gun is not likely to use RTA.

The kind of players who are not likely to be bad actors will be cut off by this contextual information.

It is easier to search for suspicious behavior with the pool rendered smaller. That is where the hand analysis takes place.

Poker profiling for security will be the future

The most common and simple spots are the ones that players tend to start learning GTO with. A5 Labs grades the spots they are interested in.

The A5 team is looking for spots that are low in entropy. It wants the biggest amount of information from the smallest number of hands.

There are a lot of places on the river where even the most knowledgeable human is likely to make a mistake. Cheaters do not have this problem. The best player will not be able to match the performance of a player who uses RTA that contains solutions for these spots. Things like that are considered to be sore thumb by the A5 Labs.

According to the co-CEO of A5 Labs, contextual information is not really reliable, but it does give you some indication of a player’s risk. Even with just two hundred hands, if you have a good baseline, it is hard not to make costly mistakes. It’s especially important when you get to the river. Even pros make mistakes here.

The process of flagging risky players would be smoothed and automated through the increased use of machine learning using, as the author says, “ai to build a much more robust system that can analyze all of this and output predictable and reliable results.”

The future of poker profiling for the sake of the environment

Games need to be fair and sustainable at the same time.

He says that amateur poker players can’t contribute to the industry because they don’t stand a chance. The lifetime of these players is not very long. The majority of the sites have a small percentage of players capturing the majority of the winnings.

A sort of rating system is one solution. Chess is an example of a game where most people would stop playing if they faced skilled players from the off. You can log into, hit play, and be matched with someone who is the same skill level. In the same way, A5 Labs envisions a future in which poker software sits you at a table with other players in your skill level.

This would allow beginners to find their feet and step up as long-term members of the poker community by keeping them from dumping their cash too quickly.

Technology has a big role to play, that’s what we think. There are places and issues that make the games not fair if you can identify skill level. Trying to help a greater range of players actually win is the broader context. We think in terms of a fairness quotient where players move closer to the break-even line, helping have a fair distribution of wins and losses, and extending the lifetime of these players.

According to A5 Labs, this is not designed to hurt pros at the expense of new players.

Operators see smart incentive schemes to ensure their professional players continue to make a strong profit as long as they contribute to engagement, fun, action, and overall sustainable practices. We are working on a loyalty scheme that rewards players for creating action.

Everyone plays a part for the good of the game in this solution.

What do you think about rehabilitation?

False positives or a kind of irrevocability are the biggest fear with a system like this. There are reassurances on both fronts from Tran.

The analogy with the credit rating system is something that I would like to use. A stable and sustainable system needs to take into account both the short and long term. You want the system to be weighted towards the most recent actions, because there are things you have done recently and things you have done historically.

In other words, time heals. A good reputation can be earned if you keep your nose clean.

Anonymity and a third party, an organization to checkmark proposed standards, like the credit industry, is what the system really needs in order to allay fears of accidental permabans and the like.

What will happen when we have a credit rating system in place? Managing the huge amount of data and allowing operators to use it without compromising anonymity is a significant problem.

In the next entry in The Future of Online Poker series, we will talk about A5’s solution for NFT avatars, which is also a solution for that.

Don’t stay away from the debate. The vision for a safer future for online poker is set out in the A5 Labs White Paper. At, you can find more information about its long-term mission to make poker secure and sustainable.


US-based startup A5 Labs has published a white paper titled ‘Advanced Technologies for Secure, Fair, and Fun Online Poker’. The paper outlines three key ideas for player profiling. There is “contextual data” for very broad, very rough categorizations, there is GTO hand analysis for pinpoint precision and there is machine learning to drive efficiency and greater accuracy.